Initial evidence of abnormal brain plasticity in anorexia nervosa: an ultra-high field study

Anorexia Nervosa has been associated with white matter abnormalities implicating subcortical abnormal myelination. Extending these findings to intracortical myelin has been challenging but ultra-high field neuroimaging offers new methodological opportunities. To test the integrity of intracortical myelin in AN we used 7 T neuroimaging to acquire T1-weighted images optimized for intracortical myelin from seven females with AN (age range: 18–33) and 11 healthy females (age range: 23–32). Intracortical T1 values (inverse index of myelin concentration) were extracted from 148 cortical regions at ten depth-levels across the cortical ribbon. Across all cortical regions, these levels were averaged to generate estimates of total intracortical myelin concentration and were clustered using principal component analyses into two clusters; the outer cluster comprised T1 values across depth-levels ranging from the CSF boundary to the middle of the cortical regions and the inner cluster comprised T1 values across depth-levels ranging from the middle of the cortical regions to the gray/white matter boundary. Individuals with AN exhibited higher T1 values (i.e., decreased intracortical myelin concentration) in all three metrics. It remains to be established if these abnormalities result from undernutrition or specific lipid nutritional imbalances, or are trait markers; and whether they may contribute to neurobiological deficits seen in AN.


Results
Socio-demographic and illness-related data. Individuals with AN did not differ from controls in terms of age. As expected, individuals with AN had a significantly lower Body Mass Index (BMI) compared to controls (Welch t = 6.057, p < 0.001) ( Table 1). Osmolality levels were within the normal range for 4/7 (57.1%) individuals with AN, while three patients had slightly higher values than the normal range 42 . Duration of illness in individuals with AN ranged between 1 and 21 years. No current psychiatric comorbidity, or past psychiatric diagnosis was identified. Only one participant reported psychotropic medication use (venlafaxine).
Global T1 values. Participants with AN and controls had equal variances distribution for total T 1 values (in milliseconds) (Levene's Test p > 0.05). A statistically significant difference emerged between groups for T 1 values (F(1,15) = 6.95, p = 0.03, η 2 = 0.29). In detail, patients with AN showed higher T 1 values than controls (Mean Difference MD = 48.55 ms, Standard Error SE = 19.80, 95% Confidence Intervals (C.I.) = 6.34, 90.77, Cohen's d = 1.26). These differences also emerged in the bootstrap post-hoc comparison (MD = 48.28 ms, Bias = −0.406, SE = 17.29, 95% bias corrected accelerated C.I. = 15.28, 85.14). See Table 2 and Fig. 1b for all details. A graphical representation of total T 1 values maps is available in Fig. 1a. Images were rendered with the ggsegDesterieux (https:// github. com/ LCBC-UiO/ ggseg Deste rieux) and ggseg 43  Based on the structural indications provided by the Principal Component Analysis (PCA), we averaged the T 1 values from depth levels 1 to 5 independent of ROIs to form a composite measure of intracortical concentration in an "inner cluster" (i.e., cluster extending from the middle of the cortical ribbon to the gray matter/white matter boundary). The corresponding measures from depth levels 6 to 10 were also averaged independent of ROIs to generate a composite measure of intracortical concentration in an "outer cluster" (i.e., cluster extending Table 1. Descriptive statistics: *Osmolality index expressed in milliosmoles/kg. Mean (standard deviation) and group differences for age and BMI are shown. Average osmolality index, EDE's global score, restraint, eating concern, shape concern and weight concern subscales score are reported for individuals with AN only. EDE, Eating Disorder Examination. + p > 0.05. www.nature.com/scientificreports/ from the middle of the cortical ribbon to the gray matter/CSF boundary). The mean cortical concentration of the inner and outer clusters were included in two separate set of analyses. See Table 3 and Fig. 1c,d for details about inner and outer cluster distributions.

Discussion
In this preliminary study, we used an innovative method based on 7 T ultra-high field MRI to examine depthdependent intracortical myelin in a population of women with AN. In accordance with our hypothesis, women with AN showed higher T 1 values across the cortical ribbon. These differences were stronger in the five outermost intracortical depth-levels, whilst they were less evident in the five inner intracortical layers. Such results may index an intracortical myelin deficit in women with AN compared to healthy controls. The use of a high-resolution MRI scanner allowed for the first time to use T 1 values as a proxy to investigate depth-dependent intracortical myelin organization in-vivo. Our results are consistent with previous findings of reduced myelin concentration in AN 27,44 , and go beyond these, showing that such a deficit is widespread and mainly affects the outer depth-levels dependent intracortical myelin organization. Travis and colleagues 27 reported a relationship between decreased fractional anisotropy (FA, defined as a marker of WM integrity) and decreased relaxation time R1 (considered as an index of myelin content) in AN adolescents. This suggests that observed WM differences in AN might be due to reductions in myelination 10,45 . However, as stated recently by Barona and colleagues in their meta-analysis 46 , differences in WM could be due to several factors, including a larger axon diameter, lower packing density of fibers, altered membrane permeability as well as a myelin deficit 47 . In fact, Travis and colleagues 27 also underlined that the most significant WM disruptions occurred where the axons showed the largest diameter and a thicker myelin shell (i.e. the corticospinal tract and the corpus callosum) 21 .
Whereas in our study higher T 1 values were found in patients with AN, in a recent study 44 performed with a 3 T MRI scanner an opposite pattern emerged, i.e., patients with AN showed lower T 1 relaxation times (i.e. time constant indicating how long the protons need to return to the equilibrium state 41 ) than controls in both gray matter and WM. Nonetheless, the authors suggested that these differences could be related to starvation-driven myelin loss 44 . Although the two interpretations seem counterintuitive, it is worth highlighting that T 1 relaxation time is strictly dependent on the physical properties of the underlying tissue 41 , including free water content 48,49 and concentration and types of macromolecules 50 such as iron content 49 and myelin 51 . Thus, to date, such methodologies based on in-vivo quantitative MRI do not allow confirmation that between group differences may be due to various factors other than myelin content. Nevertheless, it is known that while water content is directly proportional to T 1 time, iron content and myelination are inversely related to T 1 41 . This is confirmed by the fact that T 1 relaxation time is generally longer in WM, which is myelin dense 41 . While Boto and colleagues 44 did not exclude the impact of water content in the measurement of relaxation times, in our study hydration level was not Table 3. T 1 values in the inner and outer cluster across individuals with AN and controls: Analysis of Covariance. Mean (standard deviation) of average T 1 values across cortical depth-levels 1-5 (inner cluster) and 6-10 (outer cluster). Group differences in terms of F value (degrees of freedom), p value and effect size are shown. a Analyses corrected for age.

AN Controls
Group www.nature.com/scientificreports/ a confounder. Moreover, the relationship between T 1 and myelin has also been confirmed by ex-vivo data 34,39,40,51 , even in populations characterized by strong myelin loss such as multiple sclerosis 52,53 . It is known that myelin assembling persists during development and in adult life [54][55][56][57] . Animal studies highlight that the process of myelin lipid remodeling is continuous, and that the rate of change of such lipids is different throughout life 58,59 . Myelin membranes are known to have a very high lipid-to-protein ratio, with lipids accounting for at least 70% of the dry weight 2 . Myelin construction therefore requires a large amount of lipids, including cholesterol, galactolipids, plasmalogen, and fatty acids 60 . In consideration of the reduced caloric intake, decrement in intracortical myelination in AN may mirror oligodendrocytes' dysfunctions due to lack of micronutrients necessary for the synthesis of specific lipids. Nevertheless, further studies targeted on AN are needed to confirm such a claim.
A myelin deficit may also play a fundamental role in the symptomatic manifestations of AN. Animals studies suggest intracortical myelin is related to cortical functions and behavior 61 , and changes in myelin preceded changes in behavior 54,55 . Therefore several authors have suggested that intracortical myelin might be a marker of plasticity in the cortex 40,61 . Myelin damage, demyelination or oligodendrocyte loss results in a global malfunction in many neurological conditions such as multiple sclerosis, leukodvstrophies, Alzheimer's disease, stroke, cerebral palsy, traumatic brain-spinal injury and cognitive decline 62,63 . Therefore intracortical myelin loss might contribute to the neurocognitive deficits of patients with AN such as cognitive flexibility, weak central coherence, emotional processing difficulties 64 .
Further investigations will need to study closely the relationship between neurocognitive differences and myelin concentration in AN.

Strengths and limitations.
This preliminary study is the first to investigate depth-dependent intracortical myelin organization in individuals with AN. Using the high spatial resolution afforded by 7 T imaging in conjunction with a previously validated method for intracortical myelin estimation 40 we obtained information about T 1 values used as a proxy for intracortical myelin concentration across the cortical ribbon. Given the small sample size and the lack of specific a-priori assumptions, we chose not to focus on specific ROIs and this limitation should be addressed in future studies. The small sample size represents the main limitation but the current findings albeit preliminary encourage further studies in larger and more fully characterized samples. Osmolality as an index of hydration was collected in AN patients only, precluding us from including it as a covariate in our main analysis. However, correlation between osmolality and myelin concentration in the outermost depthlevels was weaker than within the inner cluster in AN patients, and only two out of seven patients with AN had abnormal osmolality levels indicative of dehydration, hence it is unlikely that dehydration fully confounds our findings. At the time of the study, the patients were all in the acute phase of illness, but duration of illness varied across our sample. Although no relationship emerged between illness duration and variables of interest, there might have been heterogeneities in the clinical sample. Although we are aware of the aforementioned limitations, we believe that our study provides promising evidence of altered intracortical myelin organization in AN.

Conclusions
In this preliminary study, we leverage a novel method for the in-vivo examination of T 1 values as an inverse index of intracortical myelin organization in AN. We found generally higher T 1 values in women with AN compared to healthy women, mirroring a widespread lower myelin concentration. These differences might be due to malnutrition and starvation, and general brain atrophy, or might be trait markers of the illness. However, the specific mechanisms (nutritional or structural) that might lead to myelin loss, and most importantly if this loss is reversible, need to be elucidated further. Moreover given the newly hypothesized role of metabolic factors in the etiology of AN 65 , whether a premorbid abnormality in myelin structure exists needs specific investigation. In a more speculative fashion, our study also raises the possibility that cognitive, visuo-spatial (and other) difficulties seen in active AN might be the result of altered intracortical myelin. Despite limitations, our findings provide an important foundation on which to build future studies. If confirmed, these results could shed new light on the neural basis of AN and on brain effects of the illness.

Methods
Participants. The study was carried out at the Icahn School of Medicine at Mount Sinai, New York. Participants were recruited amongst patients from the Mount Sinai Eating and Weight Disorders Program, the Mount Sinai Psychiatry service and from the community via flyers and adverts. Initial screen for eligibility was conducted over the phone by a research coordinator. We included female participants, with an age range from 18 to 45, who were able to provide informed consent and who spoke and understood English fluently. Patients had to have: (a) a diagnostic statistical manual of mental disorders, 5th edn (DSM-5) 66 diagnosis of AN; (b) a body mass index (BMI) between 15.5 and 18.5; (c) a history of food restriction of more than 1 year; (d) to be medically stable. Healthy controls were screened for eligibility and had to have no history of mental health disorders (including eating disorders) and no chronic medical conditions.
Exclusion criteria for all participants included any contraindication to the MRI examination (i.e., embedded or implanted metallic bodies and claustrophobia) and pregnancy.
Participants who met initial criteria for the study were invited for an in-person assessment. After providing informed consent, participants completed initial study measures and completed a urine pregnancy test. Seven female adults with current AN and 11 healthy female adults were included.
The study was approved by the institutional review committee of the Icahn School of Medicine at Mount Sinai (ISMMS). All research was performed in accordance with relevant guidelines and regulations. Patients and controls provided informed consent to participate. www.nature.com/scientificreports/ Measures. Socio-demographic data were collected using a short questionnaire. Weight and height were measured objectively to calculate BMI (kg/m 2 ) ( Table 1). Data were collected on socioeconomic status, duration of illness, and current medications in individuals with AN. The Eating Disorder Examination interview version16.0D (EDE 67 ) was used for diagnostic purposes. The EDE is a semi-structured interview considered the "gold standard" for assessing eating disorder symptoms. The EDE assesses a range of eating disorder features and yields a global score of eating disorder symptoms ( Table 1).
The SCID Screening Module 68 was administered to screen participants for other psychiatric disorders conditions. AN patients underwent a blood draw in order to establish their level of osmolality (i.e. an hydration index based on molecular weight/1 L water presence ratio expressed in milliosmoles per kilogram).

MRI acquisition.
Patients and controls were scanned at the ISMMS using a 7 T MR scanner (Magnetom, Siemens Healthcare) with a 32-channel with a Nova head coil (Nova Medical, Wilmington MA). An ultra-high resolution MP2RAGE sequence was used to acquire whole brain T1-weighted images. Acquisition parameters consisted of 0.5 mm isotropic resolution, repetition time (TR) = 5000 ms, echo time (TE) = 5.75 ms, inversion time (TI) TI1/TI2 = 900 ms/2780 ms, 224 axial slices with slab thickness 11.5 cm, field-of-view 224.5 × 203 × 112 mm 3 , and slab selective excitation and flow suppression 36 . Bias-field corrected quantitative T1 maps and T1 images were obtained from images at the two inversion times (TI1/TI2).
High resolution intracortical myelin profiling using T 1 maps. Image preprocessing followed the procedures developed and validated previously 39,40 . Skull-stripping, background-marking and alignment (using rigid 6 degrees-of-freedom registration, normalized mutual information) to a 0.4 mm MNI template using the CBS Tools (https:// www. nitrc. org/ proje cts/ cbs-tools) were applied on the T1 maps, T1-weighted and T2 images. No data were discarded due to poor quality data. Then, images were corrected for field inhomogeneities and matched to a template image 39 using 3D Slicer (https:// www. slicer. org). Images were filtered with arteries and dura segmentation, corrected for partial volume effects and segmented into gray matter, white matter and cerebrospinal fluid (CSF) using the Topology-preserving, Anatomy-Driven Segmentation (TOADS) 69 and Multiobject Geometric Deformable Model (MGDM) 70 segmentation algorithms as integrated in the CBS Tools. The CRUISE algorithm 71 was applied in order to extract the cortex. Such an algorithm is robust to white matter lesions 72 . Capitalizing on the CBS Tools' Volumetric Layering module 73 , the cortex was then dissected into 10 cortical depth-levels using a volume-preserving approach. This level-set approach generates one 2-dimensional surface per layer containing T 1 values at each surface location. Next, the 2-dimensional level-sets were transformed into 3-dimensional representations of T 1 values using the CBS Tools' Profile Sampling Module. This transformation represents each vertex T-values of each level-set surface as a column of identical T 1 values perpendicular to the surface 39,40 . The final result of this pipeline is 10 volumes of cortical profiles, one for each depth-level, for each of 7 patients with AN and 11 healthy controls. The whole process was completed within each individual's native space.
The cortex was then parcellated in the native space using Freesurfer (https:// surfer. nmr. mgh. harva rd. edu/). This parcellation was based on the pre-processed T1-weighted images alone (independent of the cortex extraction described above) and was used to obtain 148 cortical regions-of-interest (ROIs) based on the Destrieux atlas, that is particularly suitable for this type of investigation by separating gyri from sulci 73,74 . In each participant and for each cortical ROI, we estimated the absolute T 1 value as an inverse index of myelin concentration at each depth-level: so, we obtained a matrix consisting of 148 total rows (ROIs) and 10 columns (i.e. each intracortical myelin depth-level) per participant.
Statistical analyses. All demographic variables were individually checked for missing data or outliers.
Normality and equality of variances were verified using Shapiro-Wilk and Levene's tests. Group comparisons for age and BMI were carried out using two-sided Independent-samples t-tests.
With the aim of getting a single index of total intra-cortical myelin concentration per participant, we averaged the values of the 10 myelin depth-measures across all the ROIs. The mean total intra-cortical myelin concentration was compared between patients and controls using an analysis of covariance (ANCOVA) with the group as main factor and age as covariate. Further, a bootstrap post-hoc comparison based on 1000 replicates was carried out in order to get a more stable group comparison result.
A Principal Component Analysis (PCA) with an oblique rotation (Promax algorithm) was applied on the original T 1 values matrix across all participants. This matrix contained of 2664 rows (148 myelin concentration values per participant, one value per ROI) and 10 columns (10 depth-levels). PCA was applied in order to reduce the number of computations and to deal with correlated predictors (i.e. T 1 values between multiple cortical depth-levels). Bartlett's Test of Sphericity has been used to check PCA assumptions. The number of components was established through a parallel analysis 75 that compared the real eigenvalues obtained from the matrix to the eigenvalues obtained from a Monte-Carlo simulated matrix based on random data with the same size 76 . As output of parallel analysis, a scree plot of eigenvalues was used to set up a threshold of significance and reliability of components using the Kaiser criterion (i.e. eigenvalues > 1). Based on the number of components extracted, we averaged the T 1 values in different analyses. Following PCA, independent comparisons between groups were carried out by means of ANCOVA with averaged T 1 values as dependent variable, the group as the main factor, age as a covariate and a bootstrap post-hoc comparison based on 1000 replicates.
Finally, for exploratory analyses, we investigated relationships between T 1 values, BMI, osmolality and duration of illness by means of non-parametric correlations (Spearman's rho rank coefficient) with significant level set at p < 0.05 uncorrected.  Fig. 1SM). Table 4 shows the contribution of each depth-measure in each component. Specifically, T 1 values at depth levels 1 to 5 contributed to RC2, whereas those in depth levels 6-10 contributed to RC1 (a path diagram is available in Fig. 1SM). In case of participation in both components (as in the case of measures in depth levels 5 and 6), the layer was associated with the component whose expression was greater. The path diagram and scree plot available in Fig. 1SM visually confirm the contribution of each depth measure to RC1 and RC2 and the reliability of the number of components extracted from the PCA.

Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.